The expectations of cellular telephone users are increasing every day. High quality speech communication in the presence of interference (e.g., unwanted sounds from the environment in which the cellular telephone is being used) along with extended battery life are desired features in such telephones. The quality of speech transmission in cellular telephones can be improved through the provision of interference suppression prior to the uplink transmission. Known interference suppression techniques that operate on audio signals captured by a single microphone may be used but may provide limited quality improvement when a noisy audio signal has a very low signal-to-noise ratio (SNR). Moreover, some of these techniques are based on non-linear processing that may introduce musical noise artifacts into the interference suppressed signal, thus reducing speech intelligibility. Blind source separation (BSS) interference suppression techniques, e.g., principal components analysis, singular value decomposition, independent component analysis, dependent component analysis, and non-negative matrix factorization, are known in theory to improve speech quality in mobile environments in the presence of interference, but these techniques operate on audio signals captured by two or more microphones. Using multiple microphones and interference suppression based on BSS in a cellular telephone is challenging due to size and limited computational resources.